Lukas Schott

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 17

Top Topics

Discriminative Classifiers

Top Venues

Publications

Leonhard Hennicke, Christian Medeiros Adriano, Holger Giese, Jan Mathias Köhler, Lukas Schott
Mind the Gap Between Synthetic and Real: Utilizing Transfer Learning to Probe the Boundaries of Stable Diffusion Generated Data. CoRR (2024)
Cathrin Elich, Lukas Kirchdorfer, Jan M. Köhler, Lukas Schott
Challenging Common Assumptions in Multi-task Learning. CoRR (2023)
Martin Bjerke, Lukas Schott, Kristopher T. Jensen, Claudia Battistin, David A. Klindt, Benjamin Adric Dunn
Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles. ICLR (2023)
Martin Bjerke, Lukas Schott, Kristopher T. Jensen, Claudia Battistin, David A. Klindt, Benjamin A. Dunn
Understanding Neural Coding on Latent Manifolds by Sharing Features and Dividing Ensembles. CoRR (2022)
Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter Vincent Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. ICLR (2022)
Lukas Schott, Julius von Kügelgen, Frederik Träuble, Peter V. Gehler, Chris Russell, Matthias Bethge, Bernhard Schölkopf, Francesco Locatello, Wieland Brendel
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain. CoRR (2021)
David A. Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan M. Paiton
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding. ICLR (2021)
Roland S. Zimmermann, Lukas Schott, Yang Song, Benjamin A. Dunn, David A. Klindt
Score-Based Generative Classifiers. CoRR (2021)
Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel
Increasing the robustness of DNNs against image corruptions by playing the Game of Noise. CoRR (2020)
David Klindt, Lukas Schott, Yash Sharma, Ivan Ustyuzhaninov, Wieland Brendel, Matthias Bethge, Dylan M. Paiton
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding. CoRR (2020)
Evgenia Rusak, Lukas Schott, Roland S. Zimmermann, Julian Bitterwolf, Oliver Bringmann, Matthias Bethge, Wieland Brendel
A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions. ECCV (3) (2020)
Lukas Schott, Jonas Rauber, Matthias Bethge, Wieland Brendel
Towards the first adversarially robust neural network model on MNIST. ICLR (Poster) (2019)
Lukas Schott, Jonas Rauber, Wieland Brendel, Matthias Bethge
Robust Perception through Analysis by Synthesis. CoRR (2018)
Shengdong Zhang, Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah
Deep learning on symbolic representations for large-scale heterogeneous time-series event prediction. ICASSP (2017)
Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred A. Hamprecht
Learned Watershed: End-to-End Learning of Seeded Segmentation. ICCV (2017)
Steffen Wolf, Lukas Schott, Ullrich Köthe, Fred A. Hamprecht
Learned Watershed: End-to-End Learning of Seeded Segmentation. CoRR (2017)
Soheil Bahrampour, Naveen Ramakrishnan, Lukas Schott, Mohak Shah
Comparative Study of Caffe, Neon, Theano, and Torch for Deep Learning. CoRR (2015)